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Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
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Image processing library wrapper for Lua
Prymus, Jiří ; Dusíková, Hana (referee) ; Petyovský, Petr (advisor)
The thesis deals with OpenCV library and its implementation into scripting language Lua. The first part of the thesis concentrates on description of the course Computer vision MPOV and description of mathematical basics needed for further understandings. The second part describes OpenCV library and its potential usage in the MPOV. Next chapter examines the programming scripting language Lua. The description of the implementation of binding the OpenCV library to Lua language along with its overall functionality is included in the practical part of the thesis. The use of LuaCV is more comfortable thanks to Open Source projects for cross-platform compilation and distribution. Part of the thesis is also generator of Latex documentation for LuaCV binding. The last chapter deals with testing LuaCV in course MPOV and analysis of criticism from students.
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Gestural Interface for Computer Control
Burdík, Vojtěch ; Beneš, Radek (referee) ; Přinosil, Jiří (advisor)
This work focuses on the relatively new computer branch – a computer vision. Work is concentrated on object recognition, localization and reaction to specific movements. The aim is to build a program that will be able to use hand movements to control computer, to the gesture as defined by the fingers and palms respond and make it the event. The objective should be achieved without the use of special sensors or more cameras, but only with one common webcam. For the image processing function from OpenCV library were used and program was built. Evaluation of function is based on functional verification in practice, evaluation of speed, accuracy and quality of object recognition. Following the scheme, how could program for gestural controlling the computer should look, was created, and then his realization in a simple program was made. This program is able to recognize the object in an image, in this case a hand, and through an evaluation of its movements control cursor on a computer with a possibility of simulation pressing the left mouse button. Program continuously allows the documents to scroll horizontal and vertical direction. The program is very robust and work with him is very simple.
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Detection of objects for industrial robots using computer vision
Huber, Michal ; Škrabánek, Pavel (referee) ; Parák, Roman (advisor)
The aim of this bachelor thesis is to create an image processing algorithm based on data captured by camera. Introduction of this thesis deals with the current situation of object detection in industrial applications and briefly presents Raspberry Pi and OpenCV library. Following chapters deal with Raspberry Pi setup, test objects design and captured pictures modifications. Last section of these chapters is devoted to a design of an image processing algorithm. The conclusion of this thesis deals with a design of vizualization interface and also describes a laboratory experiment to test the functionality of a designed algorithm.
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Automatic Photography Categorization
Veľas, Martin ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to create an application, which is would be able to achieve sufficient precision and computation speed of categorization. Basic solution involves detection of interesting points, extraction of feature vectors, creation of visual codebook by clustering, using k-means algorithm and representing visual codebook by k-dimensional tree. Photography is represented by bag of words - histogram of presence of visual words in a particular photo. Support vector machines (SVM) was used in role of classifier. Afterwards the basic solution is enhanced by dividing picture into cells, which are processed separately, computing color correlograms for advanced image description, extraction of feature vectors in opponent color space and soft assignment of visual words to extracted feature vectors. The end of this thesis concerns to experiments of of above mentioned techniques and evaluation of the results of image categorization on their usage.
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Classification and Recognition of Pathologic Foundings in Eye Retina Images
Macek, Ján ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
Diabetic retinopathy and age-related macular degeneration are two of the most common retinal diseases in these days, which can lead to partial or full loss of sight. Due to it, it is necessary to create new approaches enabling to detect these diseases and inform the patient about his condition in advance. The main objective of this work is to design and to implement an algorithm for retinal diseases classification based on images of the patient's retina of previously mentioned diseases. In the first part of this work, there is described in detail each stage of each disease and its the most frequent symptoms. In this thesis, there is also a chapter about fundus camera, which is a tool for image creation of human eye retina. In the second part of this thesis, there is proposed an approach for classification of diabetic retinopathy and age-related macular degeneration. There is also a chapter about algorithmic methods which can be used for image processing and object detection in image. The last part of this thesis contains the test results and their evaluation. Assessment of success of proposed and implemented methods is also part of this chapter.
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OpenCV library extension
Prymus, Jiří ; Babinec, Tomáš (referee) ; Petyovský, Petr (advisor)
The thesis deals with OpenCV library and its implementation into scripting languages Lua and Matlab. The first part of the thesis concentrates on description of the OpenCV library and its usage in the course Computer vision. The second chapter examines the programming language Lua and shows its potential in certain tasks. The description of the implementation of binding the OpenCV library to Lua language along with its overall functionality is included in the third chapter of the thesis. The last chapter deals with possibilities of binding CVlib Mex in Matlab environment. A part of the thesis concentrates on implementation of great number of OpenCV functions into Lua language and mechanisms of cross-platform compilation of the project as a whole.
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Reconstruction of Fragmented Objects
Bačíková, Petra ; Beran, Vítězslav (referee) ; Španěl, Michal (advisor)
Thesis deals with reconstruction of fragmented objects. It contains a sentenious view of already realized projects with reconstruction subject. In the folowing section, the thesis describes essential methods of image processing, work with contours and corelation. There are proposed algorithms of image processing, corners detection and edges matching.
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Automatic Photography Categorization
Veľas, Martin ; Řezníček, Ivo (referee) ; Španěl, Michal (advisor)
This thesis deals with content based automatic photo categorization. The aim of the work is to experiment with advanced techniques of image represenatation and to create a classifier which is able to process large image dataset with sufficient accuracy and computation speed. A traditional solution based on using visual codebooks is enhanced by computing color features, soft assignment of visual words to extracted feature vectors, usage of image segmentation in process of visual codebook creation and dividing picture into cells. These cells are processed separately. Linear SVM classifier with explicit data embeding is used for its efficiency. Finally, results of experiments with above mentioned techniques of the image categorization are discussed.
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2D barcode recognition system
Sedlář, Martin ; Richter, Miloslav (referee) ; Petyovský, Petr (advisor)
This bachelor’s thesis deals with 2D barcode reading. At the beginning a brief overview of the most used barcodes is shown. The work mainly deals with QR codes. Their structure, composition and rules for encoding and decoding are explained. Problems with arrangement of photographic scene are solved too. C++ algorithm for QR code reading is described with usage of the OpenCV library.
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